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Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement
AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to e...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3817692/ https://www.ncbi.nlm.nih.gov/pubmed/24189230 http://dx.doi.org/10.1107/S0907444913018453 |
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author | Bibby, Jaclyn Keegan, Ronan M. Mayans, Olga Winn, Martyn D. Rigden, Daniel J. |
author_facet | Bibby, Jaclyn Keegan, Ronan M. Mayans, Olga Winn, Martyn D. Rigden, Daniel J. |
author_sort | Bibby, Jaclyn |
collection | PubMed |
description | AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided. |
format | Online Article Text |
id | pubmed-3817692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-38176922013-11-06 Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement Bibby, Jaclyn Keegan, Ronan M. Mayans, Olga Winn, Martyn D. Rigden, Daniel J. Acta Crystallogr D Biol Crystallogr Research Papers AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided. International Union of Crystallography 2013-11-01 2013-10-12 /pmc/articles/PMC3817692/ /pubmed/24189230 http://dx.doi.org/10.1107/S0907444913018453 Text en © Bibby et al. 2013 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Research Papers Bibby, Jaclyn Keegan, Ronan M. Mayans, Olga Winn, Martyn D. Rigden, Daniel J. Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title | Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title_full | Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title_fullStr | Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title_full_unstemmed | Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title_short | Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement |
title_sort | application of the ample cluster-and-truncate approach to nmr structures for molecular replacement |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3817692/ https://www.ncbi.nlm.nih.gov/pubmed/24189230 http://dx.doi.org/10.1107/S0907444913018453 |
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